We released the video to the paper "Anomaly Detection by Clustering DINO Embeddings using a Dirichlet Process Mixture", which improves efficiency of memory bank based anomaly detection methods in medical imaging.
We are thrilled to announce that two papers from the group have been accepted to MICCAI 2025 in South Korea!
"Anomaly Detection by Clustering DINO Embeddings using a Dirichlet Process Mixture” by Nico Schulthess et al. and "Conformal forecasting for surgical instrument trajectory” by Sara Sangalli & Gary Sarwin et al.!
We are happy to announce that the article "Learning to segment anatomy and lesions from disparately labeled sources in brain MRI” from Meva Himmetoglu et al. is going to appear in Medical Image Analysis journal!